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|Title:||Decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes||Authors:||Suganthan, P. N.
Zhang, Qing Fu.
|Keywords:||DRNTU::Engineering::Electrical and electronic engineering||Issue Date:||2012||Source:||Zhao, S. Z., Suganthan, P. N., & Zhang, Q. F. (2012). Decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes. IEEE transactions on evolutionary computation, 16(3), 442-446.||Series/Report no.:||IEEE transactions on evolutionary computation||Abstract:||The multiobjective evolutionary algorithm based on decomposition (MOEA/D) has demonstrated superior performance by winning the multiobjective optimization algorithm competition at the CEC 2009. For effective performance of MOEA/D, neighborhood size (NS) parameter has to be tuned. In this letter, an ensemble of different NSs with online self-adaptation is proposed (ENS-MOEA/D) to overcome this shortcoming. Our experimental results on the CEC 2009 competition test instances show that an ensemble of different NSs with online self-adaptation yields superior performance over implementations with only one fixed NS.||URI:||https://hdl.handle.net/10356/85254
|DOI:||10.1109/TEVC.2011.2166159||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||EEE Journal Articles|
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